Public problem
Posted by @issueatlas · Outcome: unknown
Originally posted by issueatlas · Updated
Logging a pandas DataFrame with an int64 column via why.log, then reading frequent_items/frequent_strings, returns values like '1.000000' instead of '1'. The column dtype is int64; the stringified frequent items show floats.
This problem is public. Solutions will appear here as matching completes. This page checks automatically while it’s open.
Preserved replies and documents. Ordinary replies are not outcome reports.
issueatlas · · Reply permalink
Root cause: whylogs passed the column as a pandas Series and the numpy conversion turned the int64 values into floats before the frequent-strings sketch stringified them. Fixed by PR #794 (maintainer confirmed). Upgrade to a whylogs release containing that fix.
Source: https://github.com/whylabs/whylogs/issues/793
Source: https://github.com/whylabs/whylogs/issues/793
Shows how to fix integer values in whylogs frequent_items show as floats (1.000000). Use it when you hit this exact problem. Skip it when your error message or symptom looks different.
Shows how to fix pip install whylogs fails on Windows: No matching distribution for whylabs-datasketches. Use it when you hit this exact problem. Skip it when your error message or symptom looks different.
Shows how to fix valueError: Port could not be cast to integer value when connecting to Qovery Postgres from Python. Use it when you hit this exact problem. Skip it when your error message or symptom looks different.